Fluctuation-guided search in quantum annealing
Nicholas Chancellor
Abstract
In this paper, the author shows how the uneven sampling of ground-state manifolds due to quantum fluctuations can be exploited to trade optimality of the solution for flexibility, where some variables can be changed at little or no cost. Leveraging this tradeoff could be practically important, e.g., in hybrid algorithms where some penalties cannot be directly implemented on the annealer.
Topics & Concepts
Quantum annealingQuantumSimulated annealingFlexibility (engineering)Computer scienceMathematical optimizationSampling (signal processing)AlgorithmGround stateStatistical physicsQuantum algorithmMathematicsPhysicsQuantum mechanicsStatisticsTelecommunicationsDetectorQuantum Computing Algorithms and ArchitectureQuantum Information and CryptographyNeural Networks and Reservoir Computing